AN ANALYSIS OF FACTORS INFLUENCING THE DEVELOPMENT
OF MODERN ROMANIAN RETAIL
Mihaela, Asandei1, Andreea, Gangone2, Cristina, Gănescu3
Abstract:
At the beginning of the millennium, Romanian trade is in an intermediate stage of a complex process of development, marked by efforts and attempts to modernize the forms of commerce. After 1995 and until now, Romanian retail market has experienced a steady increase due to the entry of international modern retail chains and to changes in the Romanian consumers’ behaviour.
Currently, Romanian retail has great development potential, being in a phase of accelerated growth. In this stage, features of modern trade forms are established, competition increases, modern retail networks are reinforced and there are still attractive implantation locations that promise attractive profit margins.
Based on the premise that there is a wide range of factors that shape modern retail, this paper analyses the impact of macroeconomic variables on the development of Romanian retail market. The research methodology was based on multifactorial regression and statistical correlation. Study results showed that Romanian retail is influenced by gross domestic product, average monthly net salary, exchange rate of the national currency against the euro, and inflation rate.
Keywords:trade, modern retail, retail cycle, life cycle of retail market.
JEL classification: L81, M31, O11.
1. The concept of modern retail
Trade is a form of human activity that has forged throughout human history the most powerful and lasting ties between countries and peoples of the world. Trade is an exchange of products, knowledge and at the same time, a way to join together different nations (Iorga, 1937).
The concept of trade is defined as the exchange relationships between producers and consumers, relations which imply buying raw materials or goods for resale in the same physical state, under conditions which favour consumers (Dayan, 1992); as a branch of national economy, trade is an economic activity which enhances the values of goods through the sale process, an intermediary between production and consumption, a vital piece in the operating mechanism of the global economic system (Abaza, 1998).
According to the concept of sustainable social development, trade is of strategic importance for a balanced development of economic and social systems in any country.
Trade is influenced by the increase of complexity, concentration and modernization of businesses, by increasing standards of living and quality of life and is conditioned by the stage of development of the material and technical infrastructure which reached a high level of mechanization, automation, cybernation, by whether modern forms of commerce are used, trade staff is better qualified, services offered to consumers are expanded, market surveys are used increasingly.
Various forms of trade, from wholesale to retail, from traditional trade to modern trade, each with features and weights influenced by the degree of development of the national economy are deployed in the market.
Over the course of the past 150 years, Western European retail sales experienced significant structural changes called the “sequence of six revolutions” (Dayan, 1992) that characterized the dynamism and prosperity of distribution activities and contrasted with cyclical crises of the economic environment of each country (Ristea, et al., 2005): the emergence of large stores (mid 19th century), the development of branches (after approximately 20 years), the creation of popular stores (between the two world wars), the
1
Associate Professor, PhD, “Constantin Brâncoveanu” University of Piteşti, mihaela.asandei@yahoo.com
2Senior Lecturer PhD, “Constantin Brâncoveanu” University of Piteşti 3
establishment of supermarkets (in the 50s), the domination of hypermarkets (early 60s), the maximization of service (early 80s).
Promoting free trade was the cornerstone of EU trade policy in the last five decades. Currently, the EU is the biggest player in international trade, carrying out 17% of global imports and exports. Trade is the key of Europe 2020 strategy and offers both less developed and richer countries benefits in terms of trade agreements and undeniable expertise in opening new markets.
In the European Union’s view, the modern concept of retail concerns trade and distribution activities and involves a variety of forms (stores, e-commerce, open markets...), sizes (from small shops to supermarkets), products (food, non-food, prescription or over the counter drugs...), legal structures (freelancers, franchisees, integrated groups...), and locations (urban / rural, central / peripheral...) (European Commission, 2010).
The complex nature of modern retail cannot be reduced to the simple dichotomy of “small traders / big distributors”. Indeed, in recent years, diversification dominated the strategies of large groups: from small neighbourhood stores to hypermarkets, through medium-sized stores such as supermarkets or the so-called “hard discount” stores.
In this regard, scholarly literature developed the wheel of retailing theory (Kotler, Keller, 2012) based on the principle of cyclicity of point-of-sale margins which focuses on distribution costs, meaning that a new form of retail distribution will be created on the market when it is able to operate in a profitable manner, practicing prices that are lower than those of competitors (Ristea, 2005).
According to this theory, the great wheel of retailing brings together four cycles corresponding to the major retail formats, namely: large shops, popular stores, supermarkets and hypermarkets. Each large retail format goes through three phases in its life cycle - launch, ascent and vulnerability.
Retail is thus very sensitive and vulnerable to the progress of its environment, but shows great ability to adapt to new market conditions. In this regard, a number of scholars have analysed the evolution of retail market using the concept of life cycle introduced in scholarly literature since the early 50s.
Thus, Davidson (Davidson et al., 1976) used this tool to define strategies for large retail formats seeking to adapt to market developments while generating high profit margins. Recently, other specialists have implemented the concept of life cycle in the retail market in general. Under this approach, the lifecycle of retail market consists of four stages: early growth and innovation stage, development stage, maturity stage, and decline stage (Perrigot and Cliquet, 2006).
In the present paper, we conducted an analysis of modern Romanian retail and brought scientific arguments regarding its positive development, in the context of contradictory developments of the overall economy.
2. Coordinates of Romanian trade during 1990-2012
Figure 1. The evolution of modern retail formats in the Romanian market
0 100 200 300 400 500 600 700 800 900
Nr. Total unităţi 1 3 6 10 13 21 32 43 56 64 109 175 252 356 443 543 651 773 Nr. Hypermarketuri 1 1 3 5 10 36 64 88 99 116 136 150 Nr. Supermarketuri 1 3 5 7 10 15 19 22 26 28 33 39 49 85 108 156 207 275 Nr. Magazine discount 1 2 4 4 32 64 100 142 194 223 257 297 Nr. Magazine cash&carry 1 3 3 6 11 18 23 27 34 36 39 41 42 48 51 51
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Source: Data processed by authors using
http://www.magazinulprogresiv.ro/pagina/314/Retaileri_internationali.html, accessed on 11thFebruary 2013.
Studies conducted in 2006 by Nielsen and GfK identified three stages in the evolution of Romanian trade until 2005. The first stage (1990-1996) was characterized by the emergence of a wide range of products on the market, by galloping inflation (1993) and a declining purchasing power of Romanian consumers. During this period the first supermarket (1995) and the first Metro (1996) opened and consumption reached a peak in 1998.
The second stage (1999-2002) is characterized by reduced consumption and diversification, the opening of the first Carrefour hypermarket (2001) and of the first discount store. The consumer credit boom, increasing consumer demands and focus on modern and online commerce mark the third stage (2003-2005). In 2003 a maximum of national consumption is reached and 2005 is a psychological milestone in the development of modern forms of trade in Romania.
During 2006-2008, Romanian retail grew steadily only to be interrupted by the economic crisis that has generated a decline that lasted until mid-2009. Romania entered the European Union in 2007 and this supported the development of retail trade by harmonizing tariffs and increasing imports.
In 2010, Romanian retail market was in the early stages of its growth (Balan, 2011) as illustrated by the fragmented nature of the market. In early 2011, the five largest retails in the Romanian market (Kaufland, Carrefour, real-, Penny Market and Plus) had a combined market share of only 22% (Vaschi, 2011), leaving room for new entries.
In 2011, the retail market in Romania grew from a situation in which traditional trade dominated to one of equal weight between traditional trade and modern commerce.
2012 was a year of diversification for Romanian retail market as every major retail chain developed a mix of different retail formats adapted to local specificities and targeting particular consumer segments. European Commission’s analysts forecast moderate growth trends for Romania in 2012-2013 and a gradual recovery of private consumption up to a growth rate of 3.4% in 2013 (Tanase, 2012).
customers, is a very attractive market for large retailers. For 2013, experts predict the opening of more than 250 new units in the retail market, current investments preparing major international retail groups for sustained capitalization and for conquering market potential during future periods of economic boom.
For 2010-2020, Oxford Economics’ analysts have predicted an average annual rate of growth of 5% (Craciun, 2011), as a result of upward trends of purchasing power, aggressive development of modern trade and changes in purchasing behaviour. These factors will contribute to the forecast growth of 62% of the retail market value, compared to an increase of 57% in Poland, 48% in the Czech Republic and 46% in Hungary (Ilie, 2013). If this forecast is achieved, Romanian retail market will begin to generate a turnover of 26 billion Euros annually.
3. Research methodology
The purpose of this research is to analyse Romanian retail developments in the context of the overall evolution of Romanian economy during 1995-2012. In this regard, we identified macroeconomic factors with major influence on the development of modern retail formats in Romania and we evaluated their impact on Romanian retail.
O1. The objective of this paper is to assess the impact of major macroeconomic variables on the dynamics of Romanian retail.
To follow the evolution of the Romanian retail market we used the number of retail units, regardless the type, as there are reliable data for the period under review. Retail turnover and increases of physical retail areas would have certainly been useful in the analysis, but there are no reliable statistical data to allow their quantification.
Out of many macroeconomic factors relevant for characterizing the state of the national economy, we used total GDP, expressed in euros, average monthly net salary (National Institute of Statistics, 2012a), inflation rate and EUR / RON exchange rate (National Institute of Statistics, 2012b) because these indicators reflect the level of development of the Romanian economy in the period under review from a double perspective: state and individual.
The values of these indicators are summarized in Table 1, but following the denomination of the national currency in 2005, data expressed in lei was normalized.
Table 1. Values of economic indicators in Romania, between 1995-2012
Year Total
number of retail units (RU)
GDP (billion
Euro) (GDP)
Average monthly net
salary (actual values)
Average monthly net
salary (normalized
values) (AMNS)
EUR / RON exchange
rate (actual values)
EUR / RON exchange
rate (normalized values) (ER)
Inflation rate (IR)
1995 1 27,4 215.791,08 21,579108 2.629 0,2629 32,3
1996 3 28,2 322.153,17 32,215317 3.862 0,3862 38,8
1997 6 31,2 636.987,83 63,698783 8.090 0,8090 154,8
1998 10 33,9 1.074.064,58 107,406458 9.989 0,9989 59,1 1999 13 33,4 1.554.903,08 155,490308 16.295 1,6295 45,8 2000 21 40,2 2.173.644,75 217,364475 19.955 1,9955 45,7 2001 32 44,8 3.053.764,50 305,376450 26.026 2,6026 34,5 2002 43 48,4 3.881.345,17 388,134517 31.255 3,1255 22,5 2003 56 50,3 4.868.270,42 486,827042 37.555 3,7555 15,3 2004 64 58,9 5.965.452,17 596,545217 40.532 4,0532 11,9
2005 109 79,2 737,83 737,83 36.234 3,6234 9,0
2006 175 97,1 1.029,17 1.029,17 3,5245 3,5245 6,56
2007 252 121,2 1.011,25 1.011,25 3,3373 3,3373 4,84
Year Total number of retail units (RU) GDP (billion Euro) (GDP) Average monthly net salary (actual values) Average monthly net salary (normalized values) (AMNS) EUR / RON exchange rate (actual values)
EUR / RON exchange rate (normalized values) (ER) Inflation rate (IR)
2009 443 115,9 862,42 862,42 4,2373 4,2373 5,59
2010 543 122,0 1.335,42 1.335,42 4,2099 4,2099 6,09
2011 651 136,4 1.642,67 1.642,67 4,23,79 4,23,79 5,79 2012 773 136,41 1.715,08 1.715,08 4,4560 4,4560 3,33
The hypotheses of the study are:
I1. Romanian retail market is influenced by GDP.
I2. Romanian retail market is influenced by average monthly net salary. I3. Romanian retail market is influenced by inflation rate.
I4. Romanian retail market is influenced by EUR/RON exchange rate.
We used a methodology that was based on the multifactorial linear regression model. In the analysed econometric model, the number of retail units is the dependent variable, macroeconomic indicators being independent variables. Data analysis was performed using statistical methods of analysis and the Data Analysis module in Excel.
The research that validates the hypothesis is the following:
RUi= b0+ b1× GDPi+ b2x AMNSi+ b3x ERi+b4x IRi +i (1)
(RU = number of retail units; GDP = total gross domestic product; ER = EUR / RON exchange rate; AMNS = average monthly net salary; IR = annual inflation rate;i= error; i = years
1995 to 2012).
Multifactorial regression model results are summarized in Table 2.
Table 2. Results of the regression function
Regression Statistics
Multiple R 0,948
R Square 0,899 Adjusted R Square 0,868
Standard Error 90,520802
Observations 18
ANOVA
df SS MS F
Significance F
Regression 4 948979,41 237244,85 28,95 0,0000002
Residual 13 106522,20 8194,02
Total 17 1055501,61
Coefficients
Standard
Error t Stat P-value Lower 95% Upper 95%
Lower 95,0%
Upper 95,0%
Intercept -119,37546 89,34785 -1,33608 0,20444 -312,39977 73,64884 -312,39977 73,64884
GDP 2,61623 1,25542 2,08394 0,05746 -0,09595 5,32841 -0,09595 5,32841
SLMN 0,34459 0,10636 3,23996 0,00645 0,11482 0,57436 0,11482 0,57436
RLE -39,46121 30,35053 -1,30018 0,21612 -105,02955 26,10712 -105,02955 26,10712
RI 0,53948 0,85228 0,63298 0,53773 -1,30177 2,38073 -1,30177 2,38073
Source: data calculated by authors
1
(r), the multiple coefficient of correlation, with a value of 0,948 is the correlation ratio that indicates a strong connection between Romanian retail and main factors of influence under analysis. The coefficient of determination - Rsquare - has a value of 0.899 and shows that 89.9% of the variance in Romanian retail can be explained by the variables taken into consideration. The adjusted correlation report shows that 0,868 of the total variance is due to the regression line, given the number of degrees of freedom. The F test shows the role of independent variables in explaining the dependent variable’s evolution. The values of the F test (28,95) and of the significance threshold (0,0000002 <0,05) show that the regression model is valid and can be used to analyse the dependence between variables.
The b0 free term, with a value of -119,37 is the point of intersection of the regression line with the OY axis. Since statistical t = -1,336 and P-value = 0,204> 0,05, it means that the coefficient is significantly different from 0, with a confidence interval of [312,399; 73,648]. The coefficient for the GDP variable, with a value of 2,61623, is positive and indicates a direct link between RU and GDP, so that an increase of 1 Euro GDP increases RU by 2,61623 points.
Because the P-value = 0,057> 0,05, the coefficient is insignificant. The coefficient for the AMNS variable, with a value of 0,344, is positive and indicates a direct link between RU and AMNS, so that an increase of AMNS by 1 leu increases RU by 0.344 points. Since the P-value = 0,00645 <0,05, the coefficient is significant, with a confidence interval of [0,114; 0,574]. The coefficient for the ER variable, with a value of -39,461, is negative and indicates a reversed connection between RU and ER, so that an increase of ER by 1 leu causes a decrease of RU by 39,461. Because the P-value = 0,216> 0,05, the coefficient is insignificant.
The coefficient for the IR variable, with a value of 0,539, is positive and indicates a direct connection between RU and IR, so that an increase of IR by one unit increases the UR by 0,539 points. Because the P-value = 0,537> 0,05, the coefficient is insignificant.
The results of the econometric model are influenced by collinearity (Adams et al., 2007), which occurs when a group of independent variables are strongly correlated. In this case, there is an overestimation of the coefficient of determination and of the estimated coefficients of dispersion, which leads to bigger intervals of confidence and may distort the interpretation of the model. Showing the impact of multicollinearity is achieved by analysing the correlation matrix of independent variables as shown in Table 3.
Table 3. The matrix of correlation of independent variables
GDP 1
AMNS 0,908726 1
ER 0,798049 0,827076 1
IR -0,60951 -0,60749 -0,69433 1
Source: Data calculated by authors
An analysis of the results indicates that there are strong positive correlations between AMNS, ER and GDP and between ER and AMNS. The correlation matrix shows a moderate to strong negative correlation between RI and the other three independent variables.
The following regression model results from the analysis of coefficients:
RU = 119,375 + 2,616 ×GDP + 0,344 × AMNS + (-39,461) × ER + 0,539 × IR +εi, (2)
The results presented in Table 2 show that the hypotheses of the study are valid and therefore Romanian retail is influenced by: GDP, average monthly net salary, exchange rate of the national currency against the euro and inflation rate.
4. Conclusions
that manage to develop the most effective global networks. Romanian retail market provides examples of such networks, from international chains to electronic commerce.
Research conducted shows that Romanian retail market is part of a positive trend, being influenced by the overall economic and social development of our country, analysed in terms of gross domestic product evolution, average monthly net salary, exchange rate and annual inflation rate. It is interesting to note that Romanian retail continued its positive development during the economic crisis of recent years, as demonstrated by attempts of major international investors to gain significant market share, which will generate substantial revenues during economic revival.
Study limitations result, on the one hand, from assessing Romanian retail only in terms of number of retail units and, on the other hand, from the small number of influencing factors being analysed. In the future, research will continue to design a methodology for calculating an index of retail development, which will be based on a larger number of determinants.
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